#test-time-alignment News & Analysis

2 articles tagged with #test-time-alignment. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AINeutralarXiv – CS AI · Jun 236/10

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Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation

Researchers propose Null-Text Test-Time Alignment (Null-TTA), a novel method for adapting text-to-image diffusion models during inference by optimizing the unconditional embedding in classifier-free guidance rather than manipulating latent variables. This approach maintains semantic coherence while achieving superior alignment to target rewards without reward hacking, establishing a new paradigm for test-time model adaptation.

AIBullisharXiv – CS AI · Jun 26/10

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T-POP: Test-Time Personalization with Online Preference Feedback

Researchers introduce T-POP, a novel algorithm that personalizes large language models in real-time by learning from user preference feedback during text generation, without requiring parameter updates or extensive pre-existing user data. The method combines test-time alignment with dueling bandits to efficiently balance exploration and exploitation, addressing the cold-start problem in LLM personalization.